Application of Yu’s wavelet and supervirtual seismic refraction interferometry to enhance first arrivals: A case study from Kuche Mountain

Abstract

The signal-to-noise ratio (S/N) of the 3D seismic data in Kuche Mountain is poor, where the first-arrival events are overlapped with random and coherent noises due to the data set collected within a challenging environment with abrupt changes in the topographical elevation. Therefore, it is difficult to carry out first-arrival picking, which in turn affects the application of tomographic inversion and static correction in this area. To face this challenge, first-arrival filtering using Yu’s wavelet and first-arrival enhancement with supervirtual seismic refraction interferometry are applied in 3D seismic data processing on the data set collected from the Kuche Mountain area. The result finds that, by using these two techniques together, the first-arrival events can be recognized easily, the first-arrival times can be picked accurately, and the amount of picked events increases greatly.